AFLP Analysis of <i>Phytophthora cactorum</i> Isolates from Strawberry and Other Hosts: Implications for Identifying the Primary Source of Inoculum
Bibliographic record
Abstract
Forty-seven isolates of Phytophthora cactorum from North America and Germany were subjected to amplified fragment length polymorphism (AFLP) analysis to investigate genetic diversity among isolates and geographical populations; 42 isolates were recovered from cultivated strawberry plants (Fragaria × ananassa), and five isolates had been recovered from plants in four other genera (Syringa, Abies, Malus, and Panax). From all isolates evaluated, 226 out of 264 markers (85.6%) were polymorphic and provided 42 unique AFLP profiles. The genetic diversity among isolates of P. cactorum from strawberry was greater than that among isolates from the other hosts. Isolates collected during recent crown rot epidemics in strawberry fields in South Carolina were genetically diverse and scattered among isolates from other geographical areas in an unweighted pair-group mean analysis (UPGMA) dendrogram. Isolates collected during recent crown rot epidemics in North Carolina also were genetically diverse, but most isolates clustered with isolates collected in 1997 from Florida strawberry fields. These data suggest that recent outbreaks of Phytophthora crown rot in the southeastern United States resulted from use of transplants already infected or infested with P. cactorum rather than from endemic populations of this pathogen, which would affect recommendations for disease management.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".